A tree felling defect elimination analysis method based on laser point cloud

Abstract

The present invention relates to the technical field of power lines, and specifically to a tree felling and defect elimination analysis method based on laser point cloud, comprising the following steps: S1: formulating a tree obstacle detection range standard; S2: synchronously collecting laser point cloud data in sections, and quickly and automatically processing the data; S3: analyzing the safe distance between power lines and vegetation points, and determining the position and range of the tree obstacle area; S4: performing single-tree segmentation on the vegetation point cloud in the tree obstacle area, and counting the number of single trees, and finally realizing accurate estimation of the number of felled trees. The present invention collects point cloud data programmatically through an unmanned aerial vehicle laser radar, and after automatic processing, it can be presented on a web page through Webgl technology. At the same time, through RGB reconstruction and comparison, combined with a tree database, automatic comparison and tree felling and defect elimination analysis are realized, and the subsequent construction conditions and the rationality of the implementation arrangement are predicted to have a clear efficiency improvement, and a high-simulation traction field construction simulation based on the unmanned aerial vehicle laser point cloud is realized.

Description

Technical Field

[0001] The invention relates to the technical field of power lines, and in particular to a tree felling and defect elimination analysis method based on laser point cloud. Background Art

[0002] For a long time, the conflict between trees and lines has been an important problem that has plagued the safe production of power companies. The "under-line trees" and "beside-line trees" in the power line channel directly or indirectly affect the safety of power supply. During the "Bolaven" typhoon in 2012, the power line tripping, pole falling and line breaking caused by the fallen trees and insufficient safety distance of illegal buildings accounted for 67.9% of the faulty lines during the typhoon, affecting the lives of residents and the normal production of industrial and commercial enterprises. At the same time, the fallen trees on the lines brought many difficulties to the power supply company for emergency repairs, and the restoration of power supply was delayed, causing certain negative effects. On the other hand, although the relevant laws have given the power supply department full power to manage the trees and obstacles in the protection area of ​​overhead power lines in accordance with the law, due to the disputes of interests among all parties, the power supply department is often greatly hindered in carrying out this work. Therefore, it is necessary to eliminate the hidden dangers of fallen trees on power lines before the power line accident occurs or during the construction of the power line.

[0003] In the prior art, there are the following problems:

[0004] (1) Existing tree felling defect analysis is mostly solved through manual identification and judgment. The lack of information technology application of tree felling defect analysis has resulted in a large amount of low-value manual labor required to complete the work of predicting the rationality of tree felling defect elimination before construction, which is inefficient and costly. ；

[0005] (2) Many power lines are located in complex terrain in the wild. Manual identification and determination of tree felling and defect elimination requires proximity to the site, which undoubtedly increases the safety risks for personnel. Summary of the invention

[0006] The purpose of the present invention is to provide a tree felling defect elimination analysis method based on laser point cloud to solve the problems raised in the above background technology.

[0007] The technical solution of the present invention is: a tree felling defect elimination analysis method based on laser point cloud, comprising the following steps:

[0008] S1: Establish the tree obstacle detection range standard;

[0009] S2: Synchronously collect laser point cloud data in different sections and process the data quickly and automatically;

[0010] S3: Analyze the safe distance between power lines and vegetation points to determine the location and scope of the tree barrier area;

[0011] S4: Segment the vegetation point cloud in the tree barrier area into individual trees and count the number of individual trees, ultimately achieving an accurate estimate of the number of felled trees.

[0012] Preferably, the tree obstacle detection range standard is used to determine the UAV laser point cloud scanning area, specifically the area within two parallel planes formed by the edges of the power conductors extending horizontally outward and perpendicular to the ground, wherein the 1-10 kV power line scanning area is 6 meters, and the 35-110 kV power line scanning area is 11 meters.

[0013] Preferably, the synchronous collection of laser point cloud data in sections is specifically to divide the large area of ​​the entire power line into several small sections according to the length unit of the power line and in combination with the actual terrain conditions, and the collection work is carried out synchronously in each small section, and a work unit is set in each small section, each work unit includes several staff members and at least one laser point cloud data collection device, and the laser point cloud data is collected by using a drone.

[0014] Preferably, the rapid and automated data processing specifically involves successively and accurately extracting the data of ground points, power line points and vegetation points, and then presenting the extracted data on a web page through Webgl technology for remote interaction, thereby achieving simultaneous processing of multiple sections.

[0015] Preferably, the method of presenting the extracted data on the web page by using Webgl technology specifically combines the drone laser point cloud model and on-site oblique photography to identify various types of construction and construction sites, conduct modeling, and produce corresponding models, so that the granularity of all component models is consistent with the real product, such as independent modeling of all hardware and spacer bars, and the model is constructed 1:1 according to the real product;

[0016] The modeling of construction details, such as line sag, is modeled according to the actual verification conditions, and dynamic prompts are given after the safety distance of each position is measured in three dimensions;

[0017] The various models and components in the construction process scene include traction machine, spanning frame, tension machine, crane, pulley block and traction rope;

[0018] Moreover, all construction details, including tower dismantling, spanning frame erection, wire laying, wire tightening and insulator hoisting, are restored to the virtual space at a 1:1 ratio with the real space.

[0019] Preferably, the modeling is specifically to use the JavaScript engine for light and shadow rendering, combine the rendering tree with the layout information to draw the actual pixels, and make full use of the ideas of caching and isolation, without consuming excessive GPU and CPU performance expenses like reflow and redrawing, and improve the animation performance through layering.

[0020] Preferably, the analysis of the safe distance between the power lines and the vegetation points and the determination of the position and range of the tree barrier area specifically involves comparing the tree barrier detection range standard with the actually collected laser point cloud data, marking the trees that meet the tree barrier detection range standard as the tree barrier area, and marking the section of the power line with the tree barrier as the tree barrier area section.

[0021] Preferably, the specific steps of performing single tree segmentation on the vegetation point cloud in the tree barrier area are to establish a tree defect elimination library and RGB comparison reconstruction in the tree barrier area, generate high-precision laser point cloud data using a drone, and then judge the object by its color, shape, outline and density, classify the high-precision laser point cloud data and existing object attributes, upload the classification information to the laser point cloud line three-dimensional visualization management and application platform, and implement a high-precision laser point cloud information generation model on the platform, disassemble the tree barrier area through the high-precision model, and separate each individual tree.

[0022] Preferably, the existing object attributes include existing tree species information, specifically tree growth rate and tree height data. Based on the characteristics of the tree species, it is determined whether the tree will cause harm to the power lines, and the harmful trees are marked as tree obstacles to achieve accurate estimation.

[0023] The present invention provides a tree felling defect elimination analysis method based on laser point cloud through improvement, which has the following improvements and advantages compared with the prior art:

[0024] First, the tree felling defect elimination analysis based on laser point cloud of the present invention has practical significance. The point cloud data is collected programmatically by the UAV laser radar. After automatic processing, it can be presented on the web page through Webgl technology. At the same time, through RGB reconstruction and comparison, combined with the tree database, automatic comparison and tree felling defect elimination analysis can be realized. The rationality of the subsequent construction conditions and implementation arrangements will be predicted to have a clear efficiency improvement, and a high-simulation traction field construction simulation based on the UAV laser point cloud can be realized.

[0025] Second, in the present invention, laser point cloud data is collected by drones, so that relevant staff can obtain on-site data remotely without being close to or approaching the tree barrier area. The work efficiency of the staff is less affected by the terrain, which is not only more efficient, but also has a higher safety factor due to being away from complex and dangerous terrain, reducing safety hazards;

[0026] Thirdly, in the present invention, by dividing the large area of ​​the entire power line, it is possible to achieve the joint cooperation of multiple points, greatly improving the efficiency of data acquisition;

[0027] Fourthly, in the present invention, the marking of the tree barrier section and the tree barrier area can realize layer-by-layer classification, and the staff can gradually refine the estimation of the number of felled trees from a large range to a small range, which is more accurate and convenient;

[0028] Fifth: In the present invention, the tree obstacle area can be accurately calculated through RGB comparison and reconstruction, and more accurate tree information can be obtained, so that single tree obstacles can be judged;

[0029] Sixth: In the present invention, by comparing and analyzing the collected data with the existing trees, not only the information of the current tree barriers can be obtained, but also the hidden dangers of tree barriers that may exist in the power line installation area in the future can be clearly identified, and ultimately an accurate estimation of the number of trees to be cut down can be achieved. DETAILED DESCRIPTION

[0030] The present invention is described in detail below, and the technical solutions in the embodiments of the present invention are clearly and completely described. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0031] The present invention provides a tree felling defect elimination analysis method based on laser point cloud through improvement. The technical solution of the present invention is:

[0032] A tree felling defect elimination analysis method based on laser point cloud, comprising the following steps:

[0033] S1: Establish the tree obstacle detection range standard;

[0034] S2: Synchronously collect laser point cloud data in different sections and process the data quickly and automatically;

[0035] S3: Analyze the safe distance between power lines and vegetation points to determine the location and scope of the tree barrier area;

[0036] S4: Segment the vegetation point cloud in the tree barrier area into individual trees and count the number of individual trees, ultimately achieving an accurate estimate of the number of felled trees.

[0037] Tree felling and defect elimination analysis based on laser point cloud has practical significance. Point cloud data is collected programmatically by UAV laser radar. After automatic processing, it can be presented on the web page through Webgl technology. At the same time, through RGB reconstruction and comparison, combined with the tree database, automatic comparison and tree felling and defect elimination analysis can be realized. There will be a clear efficiency improvement in the prediction of the rationality of subsequent construction conditions and implementation arrangements, and a high-simulation traction field construction simulation based on UAV laser point cloud can be realized.

[0038] Preferably, the tree barrier detection range standard is used to determine the UAV laser point cloud scanning area, specifically the area within two parallel planes formed by the edge lines of the power conductors extending horizontally outward and perpendicular to the ground, wherein the 1-10 kV power line scanning area is 6 meters, and the 35-110 kV power line scanning area is 11 meters; by setting a reasonable scanning area, it can be ensured that tree barriers will not hinder the power lines, and that excessive manpower and material resources will not be wasted.

[0039] Preferably, the synchronous acquisition of laser point cloud data in sub-sections is specifically to divide the large area of ​​the entire power line into several small areas according to the length unit of the power line and in combination with the actual terrain conditions, and the acquisition work is carried out synchronously in each small area, and a work unit is set in each small area, each work unit includes several staff members and at least one laser point cloud data acquisition device, and the laser point cloud data is collected by drone; by dividing the large area of ​​the entire power line, the joint cooperation of multiple points can be achieved, which greatly improves the efficiency of data acquisition.

[0040] By collecting laser point cloud data through drones, relevant staff can obtain on-site data remotely without having to approach or get close to tree barrier areas. The staff's work efficiency is less affected by the terrain, which is not only more efficient, but also has a higher safety factor as it is away from complex and dangerous terrain, reducing safety hazards.

[0041] Preferably, the data rapid automatic processing specifically extracts the ground point, power line point and vegetation point data successively and accurately, and then presents the extracted data on the web page through Webgl technology for remote interaction and realizing multi-section synchronization; WebGL is a 3D drawing protocol. This drawing technology standard allows JavaScript and OpenGL ES2.0 to be combined together. By adding a JavaScript binding of OpenGL ES2.0, WebGL can provide hardware 3D accelerated rendering for HTML5Canvas, and Web developers can use the system graphics card to display 3D scenes and models more smoothly in the browser, and can also create complex navigation and data visualization. The WebGL technology standard eliminates the trouble of developing special rendering plug-ins for web pages, and can create website pages with complex 3D structures, so as to realize the accurate modeling of ground points, power line points and vegetation points. The use of Webgl technology can perfectly solve two problems of existing Web interactive three-dimensional animation: first, it realizes the production of Web interactive three-dimensional animation through HTML script itself, without the support of any browser plug-in; second, it uses the underlying graphics hardware acceleration function to perform graphics rendering, which is realized through a unified, standard, cross-platform OpenGL interface.

[0042] Preferably, the method of presenting the extracted data on the web page by using Webgl technology specifically combines the drone laser point cloud model and on-site oblique photography to identify various types of construction and construction sites, conduct modeling, and produce corresponding models, so that the granularity of all component models is consistent with the real product, such as independent modeling of all hardware and spacer bars, and the model is constructed 1:1 according to the real product;

[0043] The modeling of construction details, such as line sag, is modeled according to the actual verification conditions, and dynamic prompts are given after the safety distance of each position is measured in three dimensions;

[0044] The various models and components in the construction process scene include traction machine, spanning frame, tension machine, crane, pulley block and traction rope;

[0045] Moreover, all construction details, including tower dismantling, spanning frame erection, wire laying, wire tightening and insulator hoisting, are restored to the virtual space at a 1:1 ratio with the real space. By establishing a 1:1 virtual space, relevant staff can obtain tree obstacle information without going to the site, which is more convenient and efficient.

[0046] Preferably, the modeling is specifically to use the JavaScript engine for light and shadow rendering, combine the rendering tree with the layout information to draw the actual pixels, and make full use of the ideas of caching and isolation, without consuming too much GPU and CPU performance expenses like reflow and redrawing, and improve the animation performance through layering; using the JavaScript engine for light and shadow rendering is not only efficient, but also low-cost.

[0047] Preferably, the analysis of the safe distance between the power lines and the vegetation points and the determination of the position and range of the tree barrier area specifically involves comparing the tree barrier detection range standard with the actually collected laser point cloud data, marking the trees that meet the tree barrier detection range standard as tree barrier areas, and marking the sections of the power lines with tree barriers as tree barrier area segments; through the marking of tree barrier area segments and tree barrier areas, layer-by-layer classification can be achieved, and the staff can gradually refine the estimate of the number of trees to be felled from a large range to a small range, which is more accurate and convenient.

[0048] Preferably, the specific steps of performing single tree segmentation on the vegetation point cloud in the tree barrier area are to establish a tree defect elimination library and RGB comparison reconstruction, and after using a drone to generate high-precision laser point cloud data, the object is judged by color, shape, contour and density, and the high-precision laser point cloud data and existing object attributes are judged and classified, and the classification information is uploaded to the laser point cloud line three-dimensional visualization management and application platform, and a high-precision laser point cloud information generation model is implemented on the platform; through RGB comparison and reconstruction, the tree barrier area can be accurately calculated, and more highly accurate tree information can be obtained, so that single tree obstacles can be judged.

[0049] Preferably, the existing object attributes include existing tree species information, specifically tree growth rate and tree height data. Based on the characteristics of the tree species, it is determined whether the tree will cause harm to the power lines, and the harmful trees are marked as tree barriers to achieve accurate estimation. By comparing and analyzing the collected data with the existing trees, not only the current tree barrier information can be obtained, but also the potential tree barrier risks that may exist in the power line installation area in the future can be clearly identified, ultimately achieving an accurate estimate of the number of trees to be cut down.

[0050] The above description enables those skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A tree felling defect elimination analysis method based on laser point cloud, characterized in that: The following steps are involved: S1: Establish the tree obstacle detection range standard; S2: Synchronously collect laser point cloud data in different sections and process the data quickly and automatically; S3: Analyze the safe distance between power lines and vegetation points to determine the location and scope of the tree barrier area; S4: Segment the vegetation point cloud in the tree barrier area into individual trees and count the number of individual trees, ultimately achieving an accurate estimate of the number of felled trees; The rapid and automated data processing specifically involves successively and accurately extracting ground point, power line point and vegetation point data, and then presenting the extracted data on a web page through Webgl technology for remote interaction, thereby achieving simultaneous multi-section processing; The method of presenting the extracted data on the web page by using Webgl technology specifically combines the UAV laser point cloud model and on-site oblique photography to identify various types of construction and construction sites, conduct modeling, and produce corresponding models, so that the granularity of all component models is consistent with the real product, all hardware and spacer rods are independently modeled, and the model is constructed 1:1 according to the real product; and the modeling of construction details and line sag are modeled according to the actual verification conditions, and dynamic prompts are given after the safety distance of each position is measured in three dimensions; the various models and components in the construction process scene include traction machines, spanning frames, tension machines, cranes, pulley blocks and traction ropes; and all construction details, including tower dismantling, spanning frame erection, line laying, line tightening and insulator hoisting, are restored to virtual space in 1:1 with the real space; The modeling specifically uses the JavaScript engine for light and shadow rendering, combines the rendering tree with the layout information to draw the actual pixels, and makes full use of the ideas of caching and isolation. It does not need to consume too much GPU and CPU performance expenses like reflow and redrawing, and improves the animation performance through layering; The analysis of the safe distance between the power line and the vegetation point and the determination of the position and range of the tree barrier area specifically involves comparing the tree barrier detection range standard with the actually collected laser point cloud data, marking the trees that meet the tree barrier detection range standard as the tree barrier area, and marking the section of the power line with the tree barrier as the tree barrier area section.

2. The tree felling defect elimination analysis method based on laser point cloud according to claim 1, characterized in that: The tree obstacle detection range standard is used to determine the drone laser point cloud scanning area, specifically the area within two parallel planes formed by the edge of the power conductor extending horizontally outward and perpendicular to the ground, where the 1-10 kV power line scanning area is 6 meters, while the scanning area for 35-110 kV power lines is 11 meters.

3. The tree felling defect elimination analysis method based on laser point cloud according to claim 1, characterized in that: The synchronous collection of laser point cloud data in sections is specifically to divide the large area of ​​the entire power line into several small sections according to the length unit of the power line and the actual terrain conditions, and the collection work is carried out synchronously in each small section. A work unit is set up in each small section, and each work unit includes several staff members and at least one laser point cloud data collection device, and the laser point cloud data is collected by using a drone.

4. The tree felling defect elimination analysis method based on laser point cloud according to claim 1, characterized in that: The specific steps of performing single tree segmentation on the vegetation point cloud in the tree barrier area are to establish a tree defect elimination library in the tree barrier area and reconstruct it by comparing and reconstructing the RGB. After using the drone to generate high-precision laser point cloud data, the object color, shape, outline and density are judged. The high-precision laser point cloud data and the attributes of existing objects are classified and the classified information is uploaded to the laser point cloud line three-dimensional visualization management and application platform. A high-precision laser point cloud information generation model is implemented on the platform. The tree barrier area is disassembled through the high-precision model to separate each individual tree.

5. The tree felling defect elimination analysis method based on laser point cloud according to claim 4, characterized in that: The existing object attributes include existing tree species information, specifically tree growth rate and tree height data. Based on the characteristics of the tree species, it is determined whether the tree will cause harm to the power lines, and the trees with harmful effects are marked as tree obstacles. Achieve accurate estimation.